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The main goal of this paper is to define and study new methods for the computation of effective coefficients in the homogenization of divergence-form operators with random coefficients. The methods introduced here are proved to have optimal…

Numerical Analysis · Mathematics 2017-11-01 Jean-Christophe Mourrat

Selecting optimal kernels for regression in physical systems remains a challenge, often relying on trial-and-error with standard functions. In this work, we establish a mathematical correspondence between support vector machine kernels and…

Quantum Physics · Physics 2026-01-05 Nan-Hong Kuo , Renata Wong

{\it Ab initio} computational methods for electronic transport in nanoscaled systems are an invaluable tool for the design of quantum devices. We have developed a flexible and efficient algorithm for evaluating $I$-$V$ characteristics of…

Mesoscale and Nanoscale Physics · Physics 2016-08-16 A. R. Rocha , V. M. García-Suárez , S. Bailey , C. Lambert , J. Ferrer , S. Sanvito

This paper considers the approximation of spatial convolution with a given radial integral kernel. Previous studies have demonstrated that approximating spatial convolution using a system of partial differential equations (PDEs) can…

Analysis of PDEs · Mathematics 2025-04-15 Hiroshi Ishii , Yoshitaro Tanaka

We introduce a numerical method for computing spectral densities, and apply it to the evaluation of the local density of states (LDOS) of sparse Hamiltonians derived from tight-binding models. The approach, which we call the high-order…

Computational Physics · Physics 2025-12-04 Jinjing Yi , Daniel Massatt , Andrew Horning , Mitchell Luskin , J. H. Pixley , Jason Kaye

We review the recent progress in the theory of inhomogeneous superconductors. It was shown that Gor'kov's self-consistency equation needs a pairing constraint derived from the Anomalous Green's function. The Bogoliubov-de Gennes equations…

Superconductivity · Physics 2007-05-23 Yong-Jihn Kim

We propose the sparse modeling approach for quasiclassical theory of superconductivity, which reduces the computational cost of solving the gap equations. The recently proposed sparse modeling approach is based on the fact that the Green's…

Superconductivity · Physics 2023-03-01 Yuki Nagai , Hiroshi Shinaoka

In this paper, we present a numerical algorithm for the accurate and efficient computation of the convolution of the frequency domain layered media Green's function with a given density function. Instead of compressing the convolution…

Numerical Analysis · Mathematics 2020-06-16 Min Hyung Cho , Jingfang Huang

In this paper, an efficient method is presented for solving three dimensional Volterra integral equations of the second kind with continuous kernel. Shifted Chebyshev polynomial is applied to approximate a solution for these integral…

Numerical Analysis · Mathematics 2016-09-28 Doaa shokry Mohamed

We introduce a general approach to traces that we consider as linear continuous functionals on some function space where we focus on some special choices for that space. This leads to an integral calculus for the computation of the precise…

Analysis of PDEs · Mathematics 2025-10-28 Moritz Schönherr , Friedemann Schuricht

Green's function plays a significant role in both theoretical analysis and numerical computing of partial differential equations (PDEs). However, in most cases, Green's function is difficult to compute. The troubles arise in the following…

Machine Learning · Computer Science 2022-04-29 Guochang Lin , Fukai Chen , Pipi Hu , Xiang Chen , Junqing Chen , Jun Wang , Zuoqiang Shi

Combining the properties of monovariate internal functions as proposed in Kolmogorov superimposition theorem, in tandem with the bounds wielded by the multivariate formulation of Chebyshev inequality, a hybrid model is presented, that…

Computer Vision and Pattern Recognition · Computer Science 2011-06-03 Shriprakash Sinha , Gert J. ter Horst

This paper introduces a probability density estimator based on Green's function identities. A density model is constructed under the sole assumption that the probability density is differentiable. The method is implemented as a binary…

Machine Learning · Statistics 2012-08-22 Peter Kovesarki , Ian C. Brock , A. Elizabeth Nuncio Quiroz

Multiple kernel learning algorithms are proposed to combine kernels in order to obtain a better similarity measure or to integrate feature representations coming from different data sources. Most of the previous research on such methods is…

Machine Learning · Computer Science 2012-07-03 Mehmet Gonen

In this work a general approach to compute a compressed representation of the exponential $\exp(h)$ of a high-dimensional function $h$ is presented. Such exponential functions play an important role in several problems in Uncertainty…

Numerical Analysis · Mathematics 2023-02-22 Martin Eigel , Nando Farchmin , Sebastian Heidenreich , Philipp Trunschke

A first principle theory of charge transport in spatially inhomogeneous quantum systems composed of any finite number of particles and subject to weak electro-magnetic fields is developed. Simple analytical expressions for the linear…

Statistical Mechanics · Physics 2007-05-23 Liudmila A. Pozhar

We describe how to apply the recursive Green's function method to the computation of electronic transport properties of graphene sheets and nanoribbons in the linear response regime. This method allows for an amenable inclusion of several…

Mesoscale and Nanoscale Physics · Physics 2013-06-18 Caio H. Lewenkopf , Eduardo R. Mucciolo

We review the method of uniqueness which is a powerful technique for multi-loop calculations in higher dimensional theories with conformal symmetry. We use the method in momentum space and show that it allows a very transparent evaluation…

High Energy Physics - Theory · Physics 2017-04-06 S. Teber , A. V. Kotikov

We study the full counting statistics of heterostructures consisting of normal metal parts connected to a superconducting terminal. Assuming that coherent superconducting correlations are suppressed in the normal metals we show, using…

Superconductivity · Physics 2009-11-10 W. Belzig , P. Samuelsson

We developed a fast numerical methodfor complex symmetric shifted linear systems, which is motivated by the quantum-mechanical (electronic-structure) theory in nanoscale materials. The method is named shifted Conjugate Orthogonal Conjugate…

Numerical Analysis · Mathematics 2007-05-23 T. Sogabe , T. Hoshi , S. -L. Zhang , T. Fujiwara